Abstract 5594: Systematic identification of the chemo-immunotherapy synergism to overcome immunotherapy resistance in cancer
Authors: Yue Wang, Yifei Wang, Xiaofei Wang, Zehua Wang, Min Zhang, Da Yang
Journal: Cancer Research (2022)

Abstract Immune checkpoint blockades (ICB) have prompted a revolution in cancer treatment, but its low response rate and resistance remain a major problem. Clinical trials have reported the combination of ICB with chemotherapy can improve patient treatment outcome, but the synergy potential of most chemo drugs with ICBs are not systematically evaluated due to the limited insight of drug induced alterations in tumor microenvironment. Here, we reported a novel algorithm termed post-treatment-based synergy prediction for chemotherapy and ICB combination (POSEIDON). POSEIDON integrates one million drug-induced transcriptomic changes of T cell and cancer cells from the Library of Integrated Network-Based Cellular Signatures (LINCS) and ICB-induced single cell transcriptomic changes of 500K cells from tumor microenvironments across multiple cancer types. Using the gene expression signatures induced by chemotherapy and immunotherapy, POSEIDON utilized a reversal-orthogonal framework to predict the chemo compound that can potentially overcome ICB resistance and improve treatment beneficial. In an anti-PD1 treated melanoma patient cohort, POSEIDON identified a group of VEGFR inhibitors and HDAC inhibitors, including tivozanib and mocetinostat, showing the highest synergy potential with anti-PD1 therapy to reverse the anti-PD1 resistance through regulating T cell activities. In a triple negative breast cancer patient cohort who received the combination of anti-PDL1 and paclitaxel, POSEIDON also predicted several HDAC inhibitors (e.g., mocetinostat) and thymidylate synthase inhibitors (e.g., trifluridine) to synergize with the combination of anti-PDL1 plus paclitaxel and reverse the combination resistance through activating the immune response in tumor microenvironment. In addition to the synergy through tumor microenvironment, POSEIDON is also capable of predicting the synergy through tumor intrinsic mechanism. POSEIDON identified the genetic inhibition of EZH2 can potentially reverse anti-PD1 resistance via upregulation of tumor antigen presentation and interferon signaling. The synergy between EZH2 inhibitor and anti-PD1 was further validated in vivo by treating the anti-PD1 resistant 4T1.2 mouse model with FDA approved EZH2 inhibitor tazemetostat and PD1 antibody. Our data showed that, while tazemetostat or anti-PD1 alone failed to inhibit tumor growth, the combination of tazemetostat and anti-PD1 can significantly reduce the tumor size and increase overall survival. Collectively, our study demonstrated that POSEIDON can provide reliable prediction of chemo-immunotherapy synergism by integrating the post-treatment transcriptomic profiles from patient tumor microenvironment and cell lines. We envision that the systematic identification of chemo-immunotherapy synergism will help cancer patients to cope with immunotherapy resistance in the short future. Citation Format: Yue Wang, Yifei Wang, Xiaofei Wang, Zehua Wang, Min Zhang, Da Yang. Systematic identification of the chemo-immunotherapy synergism to overcome immunotherapy resistance in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5594.